Data Scientist

The Data Scientist establishes client's AI and automation readiness capability, building Snowpark ML and Snowflake Cortex AI workloads that execute entirely inside the governed Snowflake environment, consistent with the SOW's requirement that AI and ML workloads never move data outside the accredited boundary.

Responsibilities

• Design and build Snowpark ML and Cortex AI workloads that support predictive analytics and intelligent automation use cases. • Ensure all AI/ML workloads execute in-platform, preserving client's data residency and accreditation boundary requirements. • Partner with the Database Architect and Data Engineers to ensure governed, high-quality data feeds AI/ML pipelines. • Support use case execution and AI-readiness deliverables during the Build phase (Weeks 9–26) and expand capability during the Scale phase. • Document model design, assumptions, and performance for client review and COR acceptance. • Advise the Engagement Lead and IT Business Analyst on AI-enabled use cases during backlog prioritization. • Experience with S3 External Stages and secure AWS-to-Snowflake data movement. • Knowledge of AWS KMS encryption and high-volume Snowflake ingestion patterns. • Understanding of MuleSoft data consumption and integration architectures.

Required Skills

Machine LearningData Science, Computer Science, StatisticsSnowflake Cortex AI Or Snowpark MLPhytonSQLAI Governance

Must-Have Traits

• Understanding of federal AI governance and data security constraints (FedRAMP, FISMA) and experience operating within them.
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
• 6+ years of applied data science / machine learning experience, including production model deployment.
• Hands-on experience with Snowflake Cortex AI and/or Snowpark ML require
• Understanding of MuleSoft data consumption and integration architectures.
• Experience with S3 External Stages and secure AWS-to-Snowflake data movement.

Nice-to-Have Traits

• Experience productionizing ML solutions in a regulated or government environment preferred